RaySearch Laboratories (Sweden)

Reirradiation is increasingly used for recurrent and new primary cancers, but dedicated planning tools are limited. We integrated deformable image registration and radiobiologically consistent dose accumulation into plan optimisation to improve plan quality and robustness, applying this approach to six lung cancer cases and comparing it with a manual, maximum point-dose method. The integrated automated approach delivered higher target doses within organ-at-risk limits, maintained robustness, and was qualitatively preferable in blinded comparison. It produced clinically acceptable dose distributions for 5/6 patients, versus 3/6 with the manual method, suggesting enhanced and potentially more efficient reirradiation planning.

A growing number of cancer patients with brain metastases can benefit from stereotactic radiosurgery (SRS) thanks to recent advances in systemic therapies which have led to improved survival. Meanwhile, selection criteria for SRS treatments are evolving to include patients with increasingly many metastases. With an increasing patient load, single-isocenter treatments on widely available C-arm linear accelerators are an attractive option. However, the planning of such treatments is challenging for multi-target cases due to the island blocking problem, which occurs when the multi-leaf collimator cannot conform to all targetssimultaneously. We propose a multi-target partitioning algorithm that mitigates excessive exposure of normal tissue caused by the island blockingproblem. The proposed algorithm considers an initial set of arc trajectories and divides (partitions) the set of targets per trajectory into smaller subsets to treat with separate back-and-forth arc passes, simultaneously optimizing both the target subsets and collimator angles to minimize island blocking. We incorporated this algorithm into a fully automated treatment planning script and evaluated it on 20 simulated patient cases, each with 10 brain metastases and 21Gy prescriptions. For each case, the script generated a series of volumetric modulated arc therapy (VMAT) plans with increasingly many arcs along the three trajectories. Each such plan was compared to four baseline plans generated with alternative heuristics for distributing targets across arcs. We also evaluated the algorithm retrospectively on six clinicalcases. Partitioning significantly improved the gradient index (GI), global efficiency index ( ) and brain compared to simultaneous treatment of all metastases. For example, the average GI improved from 5.9 to 3.3, from 0.32 to 0.46, and normal brain from 49 to 26 between 3 and 9 arcs. The baseline plans improved similarly, but the proposed algorithm was significantly better at utilizing a limited budget of arcs. All target partitioning strategies increased the total number of monitor units (MUs). The dose gradient in single-isocenter VMAT plans can be substantially improved by treating a smaller subset of metastases at a time. This requires more MUs and arcs, implying a trade-off between delivery time and plan quality, which can be explored using the algorithm proposed in thispaper.

To maximize the potential benefit of the FLASH sparing effect during treatment, normal tissue regions would ideally be irradiated only briefly, typically for a couple of hundred milliseconds. Achieving such fast proton irradiation involves a mono-energetic beam at the highest cyclotron energy and the use of 3D-printed conformal energy modulators (CEM). In ConformalFLASH, a dedicated snout is mounted on the nozzle, containing the CEM, a range shifter, and an aperture. Demonstrate that ConformalFLASH irradiation using a coarse 3D-printed CEM, defined by a geometry with spike resolution>0.5mm in any dimension, is fulfilling existing clinical dose standards. The CEM is robust to printing errors and can be reliably manufactured with unmodified commercially available 3D printers. Monte-Carlo simulations were conducted to define the 3D-printing specifications of the CEM. A variety of CEMs were then printed according to specifications. CT scans were acquired, and in-beam measurements were performed for each part, using the FLASH beam properties, the FLASH snout, and dosimetry detectors. Considering the proposed ConformaFLASH setup choice, it was possible to design coarse CEM that are both robust and easily printable using commercial technology. Over several measured cases, the 3D-printed CEM yields clinical-grade proton dose distributions. This confirms the irradiation set-up and the CEM manufacturing specifications as predefined through Monte Carlo simulations. CEM CT scans reinforce further the dosimetric results, to provide additional evidence of 3D printing quality. The dose distribution obtained through carefully specified CEM proves robust to production errors typically occurring in commercial 3D printing. The robustness opens the way to simplified manufacturing of relatively complex parts. Owing to the beam configuration, the snout, and the range shifter, the CEM was able to generate clinical-quality dose distributions. The integration of the FLASH snout with its elements on the nozzle of the proton therapy system represents an important step forward in comparison to existing state-of-the-art, facilitating easier preclinical and future clinical trial investigations.


Radiotherapy (RT) in nasopharyngeal cancer (NPC) patients presents challenges due to proximity of many anatomical structures to the target volume. Furthermore, inter-fractional changes must be considered to assure target coverage. Proton arc therapy (PAT) potentially reduces healthy tissue dose compared to IMPT and VMAT. The impact of PAT on dose to organs-at-risk (OARs), predicted acute- and late radiation toxicities and robust target coverage to inter-fraction changes in NPC patients were investigated.
Approach:
Robustly optimized PAT plans were compared to clinical VMAT and IMPT plans for 10 NPC patients treated with 70.00 Gy to the primary target (CTV 7000) and 54.25 Gy to the prophylactic lymph nodal area (CTV 5425). Integral body dose and mean and max in 0.03cc dose (Dmean and max D0.03cc) in OARs were compared. Normal tissue complication probability (NTCP) values for 22 acute and late radiation-induced toxicities were evaluated. A PAT "base approach" and nine PAT planning approaches to improve PAT inter-fraction robust target coverage were investigated. Target coverage was evaluated on in total 54 weekly repeated CT images (rCTs).
Main Results:
PAT integral dose reduced by on average 55% and 15% compared with clinical VMAT and IMPT, respectively. Compared to IMPT, average Dmean and max D0.03cc were significantly reduced in all evaluated neurological structures. Compared to IMPT, in the PAT plans Dmean was reduced most in the arytenoids, PCM medius and brainstem by on average 8.0 Gy, 6.4 Gy and 6.1 Gy, respectively and all evaluated NTCP's for both acute and late timepoint were significantly reduced. Compared with IMPT, PAT base approach target coverage on rCTs was worse. Approaches to improve PAT inter-fraction target coverage were successful, while maintaining the reduction in NTCP compared to IMPT.
Significance:
Compared to IMPT and VMAT, PAT reduces healthy tissue dose and subsequent estimated toxicity risks in NPC patients. PAT planning approaches to improve inter-fraction robustness were employed successfully, while NTCP benefits of PAT were maintained.&#xD.

BackgroundThe steep dose gradients obtained with pencil beam scanning allow for precise targeting of the tumor but come at the cost of high sensitivity to uncertainties. Robust optimization is commonly applied to mitigate uncertainties in density and patient setup, while its application to motion management, called 4D‐robust optimization (4DRO), is typically accompanied by other techniques, including gating, breath‐hold, and re‐scanning. In particular, current commercial implementations of 4DRO do not model the interplay effect between the delivery time structure and the patient's motion.Purpose: Interplay‐robust optimization (IPRO) has previously been proposed to explicitly model the interplay‐affected dose during treatment planning. It has been demonstrated that IPRO can mitigate the interplay effect given the uncertainty in the patient's breathing frequency. In this study, we investigate and evaluate IPRO in the context where the motion uncertainty is extended to also include variations in breathing amplitude.Methods: The compared optimization methods are applied and evaluated on a set of lung patients. We model the patients' motion using synthetic 4D computed tomography (s4DCT), each created by deforming a reference CT based on a motion pattern obtained with 4D magnetic resonance imaging. Each (s4DCT) contains multiple breathing cycles, partitioned into two sets for scenario generation: one for optimization and one for evaluation. Distinct patient motion scenarios are then created by randomly concatenating breathing cycles varying in period and amplitude. In addition, a method considering a single breathing cycle for generating optimization scenarios (IPRO‐1C) is developed to investigate to which extent robustness can be achieved with limited information. Both IPRO and IPRO‐1C were investigated with 9, 25, and 49 scenarios.Results: For all patient cases, IPRO and IPRO‐1C increased the target coverage in terms of the near‐worst‐case (5th percentile) CTV D98, compared to 4DRO. After normalization of plan doses to equal target coverage, IPRO with 49 scenarios resulted in the greatest decreases in OAR dose, with near‐worst‐case (95th percentile) improvements averaging 4.2 %. IPRO‐1C with 9 scenarios, with comparable computational demands as 4DRO, decreased OAR dose by 1.7 %.Conclusions: The use of IPRO could lead to more efficient mitigation of the interplay effect, even when based on the information from a single breathing cycle. This can potentially decrease the need for real‐time motion management techniques that prolong treatment times and decrease patient comfort.

Objective.A four-dimensional robust optimisation (4DRO) is usually employed when the tumour respiratory motion needs to be addressed. However, it is computationally demanding, and an automated method is preferable for adaptive planning to avoid manual trial-and-error. This study proposes a 4DRO technique based on dose mimicking for automated adaptive planning.Approach.Initial plans for 4DRO intensity modulated proton therapy were created on an average CT for four patients with clinical target volume (CTV) in the lung, oesophagus, or pancreas, respectively. These plans were robustly optimised using three phases of four-dimensional computed tomography (4DCT) and accounting for setup and density uncertainties. Weekly 4DCTs were used for adaptive replanning, using a constant relative biological effectiveness (cRBE) of 1.1. Two methods were used: (1) template-based adaptive (TA) planning and (2) dose-mimicking-based adaptive (MA) planning. The plans were evaluated using variable RBE (vRBE) weighted doses and biologically consistent dose accumulation (BCDA).Main results.MA and TA plans had comparable CTV coverage except for one patient where the MA plan had a higher D98 and lower D2 but with an increased D2 in few organs at risk (OARs). CTV D98 deviations in non-adaptive plans from the initial plans were up to -7.2 percentage points (p.p.) in individual cases and -1.8 p.p. when using BCDA. For the OARs, MA plans showed a reduced mean dose and D2 compared to the TA plans, with few exceptions. The vRBE-weighted accumulated doses had a mean dose and D2 difference of up to 0.3 Gy and 0.5 Gy, respectively, in the OARs with respect to cRBE-weighted doses.Significance.MA plans indicate better performance in target coverage and OAR dose sparing compared to the TA plans in 4DRO adaptive planning. Moreover, MA method is capable of handling both forms of anatomical variation, namely, changes in density and relative shifts in the position of OARs.